Deep Learning-Based Forward Modeling and Inversion Techniques for Computational Physics Problems, Hardback/Qiang Ren

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This book investigates in detail the emerging deep learning (DL) technique in computational physics, assessing its promising potential to substitute conventional numerical solvers for calculating the fields in real-time. After good training, the proposed architecture can resolve both the forward computing and the inverse retrieve problems. Publisher: Taylor & Francis Ltd Author(s): Qiang Ren Illustration(s): 14 Tables, black and white; 83 Line drawings, black and white; 54 Halftones, black and white; 137 Illustrations, black and white Number of pages: 180 Publication date: 2023 Dimensions: 162 x 241 x 17 Cover type: Hardback